15 citations · 19 across the 6 of their papers we have counts for
4 papers · 1 filter
Reducing Neural Architecture Search Spaces with Training-Free Statistics and Computational Graph Clustering
Thorir Mar Ingolfsson, Mark Vero, Xiaying Wang +3
The computational demands of neural architecture search (NAS) algorithms are usually directly proportional to the size of their target search spaces. Thus, limiting the search to h…
SNE: an Energy-Proportional Digital Accelerator for Sparse Event-Based Convolutions
Alfio Di Mauro, Arpan Suravi Prasad, Zhikai Huang +3
Event-based sensors are drawing increasing attention due to their high temporal resolution, low power consumption, and low bandwidth. To efficiently extract semantically meaningful…
Training Quantised Neural Networks with STE Variants: the Additive Noise Annealing Algorithm
Matteo Spallanzani, Gian Paolo Leonardi, Luca Benini
Training quantised neural networks (QNNs) is a non-differentiable optimisation problem since weights and features are output by piecewise constant functions. The standard solution…
ZippyPoint: Fast Interest Point Detection, Description, and Matching through Mixed Precision Discretization
Menelaos Kanakis, Simon Maurer, Matteo Spallanzani +2
Efficient detection and description of geometric regions in images is a prerequisite in visual systems for localization and mapping. Such systems still rely on traditional hand-cra…